Classifications

• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
  • G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
  • G01S7/52004—Means for monitoring or calibrating
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S1/00—Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith
  • G01S1/72—Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith using ultrasonic, sonic or infrasonic waves
  • G01S1/76—Systems for determining direction or position line
• • G—PHYSICS
  • G01—MEASURING; TESTING
  • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
  • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
  • G01S15/87—Combinations of sonar systems
  • G01S15/874—Combination of several spaced transponders or reflectors of known location for determining the position of a receiver

Definitions

• the present invention relates to acoustical metrology systems and methods used for the positioning of underwater structures and / or for the navigation of marine or submarine vehicles. More specifically, the invention relates to a method and a metrology system for calibrating the geometry of a network of immersed acoustic beacons and simultaneously navigation of a marine or underwater vehicle with respect to this network of beacons .
• Subsea acoustic metrology systems and methods are commonly used to determine the relative positions and orientations of two submerged structures to which acoustic beacons are attached.
• Each acoustic beacon is provided with at least one transmitter or acoustic transponder, adapted to emit an acoustic signal specific to each beacon.
• the acoustic beacons are assumed to be fixed relative to one another.
• the acoustic beacons can be fixed on the sea floor or on submerged equipment such as two ends of sections of a submarine pipeline that is to be connected by a pipe.
• a network of beacons is understood to mean a plurality of immersed acoustic beacons that are spatially distributed over a beacon field.
• Tags can be located in a two or three-dimensional tag field.
• the geometry of a network corresponds to the set of spatial positions with two or three dimensions of each of the beacons of this network, for example represented in the form of Cartesian coordinates (XYZ) where Z represents the depth of immersion.
• Underwater acoustic metrology systems and methods also provide measures to assist navigation of surface or submarine vehicles equipped with transmitters and / or acoustic receivers to determine the position of the vehicle in relation to a network.
• fixed beacons whose positions are previously calibrated.
• LBL Long Base Line
• the inertial navigation systems are based on the use of an inertial unit comprising three accelerometers and three gyroscopes that integrate the acceleration and rotation measurements to deduce the displacement of a vehicle in three dimensions and its current position with respect to a reference frame.
• hybrid navigation systems that combine an inertial navigation system and one or more other Doppler Velocity Log (DVL) sensors, acoustic distance measuring sensor and / or immersion depth sensor.
• DVD Doppler Velocity Log
• the simultaneous measurements of the position of the mobile and the beacons are obtained by a data processing generally based on a Kalman algorithm merging the distance information, speed compensated attitude measurements and / or of immersion depth.
• FIG. 1 shows schematically a LBL type system according to the prior art.
• the LBL system comprises a beacon network 10 formed of fixed beacons 11, 12, 13, 14, 15, 16.
• a remotely operated vehicle (ROV) is equipped with an acoustic distance meter 21 embedded.
• ROV remotely operated vehicle
• the LBL system uses only acoustic distance measurements, or more precisely acoustic time-of-flight measurements converted into distances by a multiplicative factor based on an average estimate of the acoustic wave velocity between the mobile and the beacons or better by velocity profile of the acoustic waves between the mobile and the beacons, the velocity profile being in particular a function of the immersion depth of the beacons.
• a first phase we seek to calibrate the geometry of a network of beacons of an LBL system, that is to say to determine the relative positions of the beacons of a network comprising a number Nb of beacons, where Nb is an integer.
• Nb is an integer.
• One or more of the tags may for example be attached to submerged structure elements whose relative positions are to be determined, for example pipeline ends to be connected.
• the calibration of the beacon network geometry is obtained by a series of direct distance measurements between the beacons.
• the second tag 12 defines one of the axes, for example the X axis, and is positioned at (0, y2, z2).
• the maximum possible number of direct measurements between two tags is: Nb * (Nb-1) / 2.
• Nb * (Nb-1) / 2 the number of unknowns is 2 + 3 * (Nb-2).
• Nb * (Nb-1) / 2 must therefore be greater than or equal to (3 * Nb) -4, which gives Nb greater than or equal to 6.
• Nb * (Nb-1) / 2 must therefore be greater than or equal to (3 * Nb) -4, which gives Nb greater than or equal to 6.
• Nb * (Nb-1) / 2 must therefore be greater than or equal to (3 * Nb) -4, which gives Nb greater than or equal to 6.
• Nb * (Nb-1) / 2 must therefore be greater than or equal to (3 * Nb) -4, which gives Nb greater than or equal to 6.
• 3D mode it therefore, at least six tags are required to fully determine the relative positions of the beacons of a network of an LBL system.
• the relative position of the mobile 20 with respect to the beacon network 10 is obtained by trilateration from the distance measurements between the mobile and the beacon network.
• the mobile must be able to communicate with at least three tags.
• FIG. 2 schematically shows a system of USBL or SBL type according to the prior art.
• a mobile system 20 is provided with an acoustic transmitter 21, a mini network of acoustic sensors 22 in reception and an attitude center 23.
• a beacon 1 1 (fixed or not) comprises an acoustic transducer adapted to receive an acoustic signal emitted by the acoustic transmitter of the mobile system 20 and to transmit in response an acoustic signal detected by the mini-array of sensors 22 and by the attitude unit 23 of the mobile 20.
• USBL system (or SBL) provides, for each interrogated beacon, the distance measurement d between the mobile 20 of the beacon 1 1 and the direction relative to a horizontal line H via the inclination angle ⁇ .
• the USBL system is coupled to a GPS system (or other system providing an absolute position) to calibrate the absolute position of the tag 1 1 being interrogated.
• the USBL system is positioned by interrogating the fixed beacon 1 whose position is known. A single tag 1 1 is sufficient for navigation. However, the integration of an attitude center and an acoustic sensor remains complex.
• FIG. 3 diagrammatically represents a hybrid or inertial coupled navigation system comprising an inertial navigation unit (INS) 26 coupled to at least one other sensor, for example an acoustic distance measuring sensor 21.
• the inertial unit 26 provides the displacement of the mobile with respect to an initial position from the rotation measurements and by double integration of the accelerations.
• TINS is coupled to one or more other measurement systems: speed measurement 25 obtained by log Doppler (DVL), immersion depth sensor 24, acoustic sensor 21 measuring distance relative to one or more tags 1 1, 12 of known or unknown positions.
• Inertial coupled type systems therefore use a displacement sensor (or speed) provided by the inertial unit generally coupled to acoustic sensors for measuring distance 21, immersion depth 24 and / or tidal amplitude. .
• an inertial coupled system simultaneously determines the estimation of the mobile position and the estimation of the position of the one or more tags 1 1, 12 constituting the network of tags 10.
• the calibration and navigation are performed simultaneously.
• the algorithm implemented for the calibration and navigation of an inertial coupled system is generally a Kalman algorithm which merges the information provided by the inertial unit 26 and the measurements of one or more auxiliary sensors to determine at a time. the position of the mobile 20 and that of the beacons 1 1, 12.
• This type of algorithm is well known by the acronym SLAM (Simultaneous Localization and Mapping).
• an inertial coupled system requires at least one inertial unit and one or more other sensors.
• an inertial coupled system remains sensitive to the drifts of the inertial unit.
• the fabrication of an inertial coupled system is relatively complex and requires a relatively long alignment phase.
• the different metrology systems and processes for calibration and existing navigation are complex systems that typically incorporate several different measurement techniques.
• the calibration phases of LBL, SBL / USBL or coupled inertial systems are usually long and complex.
• the present invention aims to overcome these disadvantages and to provide a system and a method of navigation and calibration simpler to implement and which is compatible with a reduced number of sensors. More precisely, the invention proposes a method of metrology for the calibration of the geometry of a network of underwater acoustic beacons, the network comprising an integer number Nb of fixed beacons and spatially delimiting a field of two-dimensional beacons or respectively three-dimensional, each of the acoustic beacons comprising means for transmitting and / or receiving acoustic signals, the metrology method implementing a mobile, the mobile having means for interrogating and receiving the acoustic signals respectively from each of the network beacons, the metrology method comprising the following steps:
• Nm series of Nb acoustic measurements of relative distance between the mobile and respectively each Nb of the network with Nm integer greater than or equal to three and Nb greater than or equal to three for a two-dimensional calibration and respectively Nm an integer greater than or equal to eight and Nb greater than or equal to four for a three-dimensional calibration; the acquisition of the series of acoustic measurements being performed dynamically during a movement of the mobile to a series of Nm successive positions;
• the method further comprises an initial step of estimating an approximate value of the relative positions of each beacon in the beacon field and estimating an approximate value of the position of the mobile relative to the beacon field and step of acquiring the series of acoustic measurements of relative distance between the mobile and respectively each of the Nb beacons of the network is performed during a movement of the mobile around the approximate position of the beacon field;
• the displacement of the mobile during the measurement acquisition step is carried out according to a curve or a portion of circular, elliptical or rectangular curve around the approximate position of the beacon field;
• the metrology method further comprises a step of determining the difference in immersion depth between tags
• the metrology method further comprises a measurement of the immersion depth of each of the tags and the mobile;
• the method of metrology includes a step of compensating for changes in depth of immersion of the beacons and the mobile according to the tides, said compensation being deduced preferably from a tide gauge or a tidal prediction model;
• the metrology method simultaneously makes it possible to navigate the mobile, and the step of executing an algorithm for minimizing the digital function C makes it possible to deduce therefrom an estimate of the relative position of the mobile with respect to the estimated values of the variables representative of the relative positions of the Nb beacons of the beacon network.
• the metrology method further comprises:
• the invention also relates to a metrology device for calibrating the geometry of a network of underwater acoustic beacons, the network comprising an integer number Nb of fixed beacons and spatially delimiting a beacon field, each of the acoustic beacons comprising means for transmitting and / or receiving acoustic signals, the metrology device comprising a mobile, the mobile comprising means interrogating and receiving the acoustic signals respectively from each of the network beacons.
• the metrology device comprises a computer configured to: e) receive Nm series of Nb acoustic measurements of relative distance between the mobile and respectively each beacon of the network, with Nm whole number greater than or equal to three and Nb higher or equal to three for a two-dimensional calibration and respectively Nm integer greater than or equal to eight and Nb greater than or equal to four for a three-dimensional calibration; said series of acoustic measurements being dynamically acquired during movement of the moving body to a series of Nm successive positions; f) calculating a numerical function C as a function, on the one hand, of the series of acoustic measurements of relative distance and, on the other hand, of variables representative of the relative positions of the beacons in the field of two-dimensional or three-dimensional beacons;
• the computer is furthermore configured for:
• the metrology device further comprises a sensor for the immersion depth of the mobile and means for measuring the difference in immersion depth between beacons or means for measuring the immersion depth of each of the tags; and / or a tide gauge or means for calculating the amplitude of the tides adapted to compensate for variations in immersion depth of the mobile and beacons as a function of the tides.
• the invention will find a particularly advantageous application in the calibration of a network of acoustic beacons and in the navigation of a remotely controlled surface or submarine vehicle.
• the invention advantageously makes it possible to calibrate the geometry of a network of beacons without reference to an absolute metrology device (GPS or other type) while at the same time ensuring the navigation of a mobile with respect to this network of beacons.
• the present invention also relates to the features which will emerge in the course of the description which follows and which will have to be considered individually or in all their technically possible combinations.
• FIG. 1 schematically shows a navigation system type LBL according to the prior art
• FIG. 2 diagrammatically represents a navigation system of the USBL or SBL type according to the prior art
• FIG. 3 represents an inertial coupled type navigation system comprising an inertial navigation unit (INS) coupled to at least one other sensor;
• INS inertial navigation unit
• FIG. 4 represents a 3D positioning system according to one embodiment of the invention.
• FIG. 5 represents a 2D positioning system according to another embodiment of the invention.
• FIG. 6 diagrammatically represents a synopsis of a navigation and calibration processing algorithm according to the invention.
• FIG. 7 represents an example of a series of measurements of distances from a mobile to a network of three beacons as a function of time
• FIG. 8 schematically represents a two-dimensional map illustrating the trajectory of a mobile around a field of beacons to approximately determine the positions of the beacons
• FIG. 9 represents a measurement of the differences in the distances between two beacons A and B during a trajectory of the mobile as illustrated in FIG. 8.
• FIG. 4 represents a submarine acoustic metrology device in 3D according to one embodiment of the invention.
• a mobile 20 comprises a computer 28 and at least an acoustic distance sensor or distance-meter 21 adapted to interrogate a network 10 of fixed acoustic beacons 1 1, 12, 13, 14.
• the device can also operate in "pinger" mode where the beacons transmit acoustic signals at a predefined rate synchronously with a reference clock, and the mobile receives the signals transmitted by the beacons, as well as the signal of the reference clock.
• the computer 28 is configured to execute the computer implementation of a 3D mode algorithm which simultaneously estimates the three-dimensional geometry of the acoustic beacon network 1 1, 12, 13, 14 and the three-dimensional position of the mobile 20 relative to with tags 1 1, 12, 13, 14.
• the distance-meter 21 emits an acoustic signal common interrogation and each tag 1 1, 12, 13, 14 responds with its own code.
• the distance-meter 21 thus measures the distances d 1: d 2, d 3 and d 4 between the mobile 20 and respectively each of the beacons for 1 1, 12, 13, 14 at a series of instants f or recurrences of measurement.
• the algorithm in 3D mode can only use acoustic measurements.
• the device in 3D mode does not require any additional sensors, such as an inertial unit, an attitude unit or a Doppler log (DVL).
• the beacon network 10 comprises three fixed beacons 1 1, 12, 13.
• the beacon network is two-dimensional, the three beacons being contained in a same plane and not aligned.
• the mobile system 20 comprises a calculator 28, a distance-meter 21.
• the mobile system 20 is further provided with an immersion sensor 24.
• the immersion depth of the beacons 1 1, 12, 13 is assumed to be known.
• the computer 28 is configured to execute the computer implementation of a 2D mode algorithm which simultaneously estimates, in horizontal projection, the geometry of the beacon network 10 and the position of the mobile 20 relative to the beacons.
• an immersion sensor 34 located at a fixed position and which records or transmits the value of the depth of immersion of this sensor. depending on the variations due to the tides or in a variant using tags provided with an immersion sensor and able to transmit this information to the mobile by a telemetry means.
• FIG. 6 diagrammatically represents an example of an acquisition and processing algorithm according to an embodiment of the invention to enable the calibration of the geometry of a beacon network and the navigation aid of a mobile in providing the relative position of the mobile with respect to this beacon network.
• the metrology process comprises the following steps:
• a step 50 of interpolation for example linear, distances (optional);
• a step 90 of estimating the position of the mobile with respect to the network of beacons is a step 90 of estimating the position of the mobile with respect to the network of beacons.
• the calibration mode operates dynamically during a movement of the mobile system 20.
• the calibration is performed at the same time as the navigation.
• the metrology process combines the calibration and navigation modes.
• the method is then applied recursively, new data acquisitions allowing on the one hand to refine if necessary the estimation of the geometry of the network of tags and on the other hand to determine a new estimate of the position of the mobile.
• the navigation of the mobile can also be performed by a conventional trilateration algorithm.
• step 30 the mobile system 20 acquires N series of acoustic measurements of distances d 1: d 2 , cf 3 ... d N between the mobile 20 and respectively each of the beacons 1 1, 12, 13 ... of the tag network 10 as a function of time.
• a first series of distance measurements is acquired between the mobile and the first beacon 11 for a series of recurrences of measurements, during the movement of the mobile.
• a second series of distance measurements is acquired between the mobile and the second beacon 12 for a series of recurrences of measurements during the same movement of the mobile.
• N series of Nb distance measurements are thus acquired between the mobile and each of the Nb beacons of the network as a function of time, during the movement of the mobile.
• Acoustic distance measurements are conventionally made from acoustic measurements of flight time taking into account the speed of the marine environment or, preferably, the velocity profile between the sensor 21 and the beacons 1 1, 12, 13, 14.
• Nm be the number of positions of the mobile as a function of time and Nb the number of acoustic beacons 1, 2, 3 possibly 4.
• the number of recurrences or measurement points Nm must be greater than a minimum value explained in the following paragraphs. The more Nm increases, the more the redundancy of the distance measurements increases and ultimately the more the measurement accuracy increases.
• Nb series of Nm recurrences are thus available, forming a series of Nm.Nb acoustic measurements of distances for Nm variable positions of the mobile with respect to the network of beacons.
• Nm the minimum number of points in this series of Nm.Nb measures.
• Nm the number of recurrences corresponding to as many successive positions of the mobile and Nb the number of beacons.
• Nm and Nb are positive integers.
• the number of beacons Nb is greater than or equal to 4.
• the number of recurrences Nm is greater than or equal to 8.
• the minimum number of points in the acoustic measurement series in 3D mode is therefore 32, for 4 beacons.
• the number of beacons Nb is equal to 4
• the number of recurrences Nm is greater than or equal to 6.
• the minimum number of points in the series of acoustic measurements in 2D mode 1 ⁇ 2 is therefore 24, for 4 tags.
• the minimum number of tags is four in 2D 1 ⁇ 2 or 3D mode, and three in 2D mode.
• the calibration method uses a series of independent acoustic measurements corresponding to variable positions of the mobile 20 with respect to the beacon network to determine the geometry of the beacon network.
• mobile 20 is in motion during the calibration procedure. With the mobile in motion, the series of measurements acquired over time represents a series of measurements at variable positions of the mobile 20 with respect to the beacon network.
• the step 40 of filtering the distance measurements the purpose of which is to reject the aberrant acoustic measurements caused for example by multiple paths of the acoustic waves between the mobile 20 and an acoustic beacon.
• Vmax typically 1 to 2m / s.
• the measurement filtering step 40 thus makes it possible to eliminate the aberrant acoustic measurement points of distances between the mobile and each of the beacons.
• the interpolation step 50 which is intended to provide measurements of the distances of the mobile relative to each of the beacons at the same instant t, whatever the distance between the mobile and these tags.
• the interpolation can be for example linear. Any other method of parabolic polynomial interpolation using spline functions is suitable.
• Dmax be the maximum distance between two beacons 1 1, 12 of the network to be calibrated.
• the mobile moves from 2 * Dmax * V / c.
• V 1 m / s
• dT 0.2s
• a maximum displacement of mobile 20cm If the speed of mobile 20 is constant in direction and normal during dT, the error made by linear interpolation of the distance at step 50 is negligible: thus to obtain an accuracy of 2 cm, a nonlinearity ⁇ 10 %.
• FIG. 7 schematically represents measurements of distance between a mobile and three acoustic beacons as a function of time, after filtering the acoustic data and interpolation between measurement points of a series of measurements, represented by crosses. .
• the measured distances are interpolated at the same reception time (see Figure 7).
• the dotted curve represents the measurement of distance between the mobile and a first beacon 11 after filtering and interpolation; the curve in solid line represents the measurement of distance between the mobile and a second tag 12 after filtering and interpolation; the dashed curve represents the measurement of distance between the mobile and a third beacon 13 after filtering and interpolation.
• the three circles correspond respectively to a measurement of one of the three distances interpolated at a time t, -.
• the interpolation step makes it possible to replace the outliers that have been eliminated in the filtering step by interpolated measurement points.
• the interpolation step makes it possible to provide measurements of the distance of the mobile to the different beacons at the same time t arbitrary, although the arrival times of the different acoustic signals of the different beacons are generally all different.
• Nb series of measurements of distances from the mobile to each beacon of the beacon network are thus available at a series of times t, -.
• the time interval between two measurements is chosen to be of the order of one second for a measurement series that can reach a few hundred or even thousands of recurrences, which corresponds to an acquisition time of typically a few tens of minutes.
• the minimum number Nm of points of the series of measurements is greater than or equal to 8 in 3D mode, and respectively greater than or equal to 3 in 2D mode, as detailed in the paragraph detailing the acquisition of the data.
• the series of interpolated distance measurements comprises at least a series of Nm distance measurements for each beacon of the network.
• the maximum number of measurement points Nm is as previously indicated of the order only a few hundred or even thousand of measurements.
• the computer seeks to determine the geometry of the beacon network without knowing the position of the mobile.
• Step 60 relies on executing the computer implementation of an algorithm to determine the positions of the tags.
• This algorithm is based on the computation and minimization of a mathematical function, classically called the cost function C (y2, x3, y3) for a series of measurements at a series of instants t, -.
• the cost function is obtained by eliminating the coordinates (x, y) of the mobile between the three equations obtained at each recurrence
• the global cost function C is independent of the coordinates (x, y) of the mobile.
• step 70 the computer 28 minimizes this cost function.
• a known minimization algorithm such as a Levenberg Marquart gradient minimization algorithm, or a global Monte Carlo, genetic minimization method. The convergence is even faster than the initial values of position of the beacons are precise. In the case where the initial position information of the beacons is not available, an initialization procedure must be undertaken. A simple method for obtaining initial estimates of beacon positions is described below in the "Beacon Position Initialization Mode" section.
• the result of this minimization provides an estimate of the relative positions of the Nb network tags in the beacon field mark. This provides the calibration of the beacon network (step 80).
• the calibration mode operates dynamically that is to say during the movement of the mobile system 20.
• the approximate position of the beacon network is generally known with an accuracy of a few meters or a few tens of meters before starting the calibration.
• the movement of the mobile during the calibration is carried out along a path that surrounds the beacon field, that is to say a space zone comprising all the beacons of the network, whose position is known approximately.
• the trajectory of the mobile is preferably symmetrical around the network of tags, for example circular, or square. In 3D mode you have to make sure that the mobile is not navigating in the beacon plan.
• This trajectory around the beacon network makes it possible to reduce the errors of bias with respect to each of the beacons: bias induced by a bad measurement of immersion or speed, for example. Indeed, to convert the flight time measurements into acoustic distance, we usually use an average speed.
• the trajectory around the beacon network thus makes it possible to average the errors due to the average speed.
• the distance between the transponders of the beacons of the network is generally between 20 meters to a hundred meters.
• the distance between the mobile and the beacon network is generally less than a few hundred meters.
• the calibration method of the invention makes it possible to estimate the relative position of the beacons with an accuracy of the order of 5 to 10 centimeters, regardless of the distance between the mobile and the beacon network.
• all the beacons are not necessarily acoustically visible from the mobile, the aberrant measurement points being filtered by the processing algorithm and replaced by interpolated points.
• the calibration of the geometry of the beacon network does not require any measurement of direct distance between the beacons.
• the calibration method therefore imposes no acoustic visibility constraints between the beacons.
• the modes to 3D and 2D 1 ⁇ 2 can be generalized from the mode to 2D.
• the unknowns are the 3D position (x, y, z) of the mobile with respect to the beacon field and the 2D geometry of the beacon network.
• the first beacon B1 is the reference beacon.
• B1 (0,0,0), B2 (0, y2, z2), B3 (x3, y3, z3) and B4 (x4, y4, z4) be the coordinates of the 4 tags.
• the relative immersion depths between beacons are assumed to be known: the values of z2, z3 and z4 are therefore assumed to be known.
• the unknowns of the system are then the 5 parameters (y2, x3, y3, x4, y4).
• the cost function is obtained by eliminating the coordinates (x, y, z) of the mobile between the four equations obtained at each recurrence:
• the unknowns are the 3D position (x, y, z) of the mobile with respect to the beacon field and the 3D geometry of the beacon network.
• the first beacon B1 is the reference beacon. Let B1 (0,0,0), B2 (0, y2, z2), B3 (x3, y3, z3) and B4 (x4, y4, z4) be the coordinates of the 4 tags, then the unknowns of the system are the 8 parameters (y2, z2, x3, y3, z3, x4, y4, z4).
• the cost function is obtained by eliminating the coordinates (x, y, z) of the mobile between the four equations obtained at each recurrence. The equations are identical to the previous case in 2D 1 ⁇ 2 mode.
• the position of the beacons is obtained by minimizing a cost function. To ensure convergence it is better to have a good estimate of the initial tag position values.
• the geometries of offshore structures are known to a few meters at worst which is sufficient.
• Figures 8 and 9 illustrate a simple method for determining them.
• the mobile 20 performs a trajectory 29, shown in dashed lines in FIG. 8, which encompasses the whole of the beacon field, while making a measurement of the differences in the distances between beacons along this trajectory 29 as described.
• the mobile 20 describes a path 29 around the three tags A, B, C in the direction indicated by the arrow.
• FIG. 9 represents the measurement in absolute value of the difference in distance between the beacons A and B:
• the system calculator can update the position of the network by means of the equations (Eq 1 .a and Eq 1 .b) and from this new estimate of the geometry of the network, provide an estimate of the position of the mobile by applying for example the equation Eq 1 .a (step 90).
• the metrology device of the invention has the advantage of allowing the calibration of a beacon network using only distance measurements, or more precisely flight time measurements between a mobile equipped with a distance-meter interrogating a network of fixed beacons.
• the mobile is also equipped with an immersion sensor
• the device can use distance measurements combined with immersion depth measurements.
• the device simultaneously estimates the geometry of the network of fixed beacons (metrology function for calibration) and the position of the mobile relative to the network (navigation function). No prior knowledge about the position of the beacons and the mobile is necessary.
• the system estimates the position of the mobile and the network geometry by moving around and / or within the beacon field.
• the proposed device provides significant benefits for the metrology function in comparison with the different prior devices.
• the metrology device of the invention offers greater simplicity and speed of implementation.
• the acoustic beacons of the network can be arranged without any acoustic visibility constraint between beacons.
• all the beacons of the network must be arranged in such a way as to communicate with each other in pairs for the calibration.
• the device of the invention can operate with a network having a smaller number of deployed tags. In 3D mode, only four tags are required according to the invention, instead of at least six tags in a LBL system in 3D mode. In 2D mode, the device of the invention requires the same minimum number of three tags as a 2D LBL device.
• the device of the invention is however not limited to a number Nb of tags and can operate with a network of tags comprising more tags than the minimum number of tags defined above according to the configuration in 2D, 2D1 mode. / 2, or 3D.
• the device of the invention thus imposes less relative position constraints of the acoustic beacons while offering the possibility of simultaneously performing the calibration of a beacon network and the navigation of a mobile.
• the metrology system of the invention offers greater simplicity: the device of the invention does not necessarily require Loch Doppler DVL or immersion sensor, or even tide gauge, if you deploy four tags in 3D mode.
• the metrology system of the invention Compared to USBL and SBL systems, the metrology system of the invention also offers greater simplicity, since it does not require a central attitude.
• the method of the invention may advantageously be implemented on old acoustic devices of the LBL type for example, replacing another method of calibration and / or navigation.
• the device and the method of the invention offer a resolution of the centimeter order which is sufficient for submerged structures positioning applications equipped with beacons and for the navigation of a mobile, and makes it possible to perform a calibration in one lap fast time typically less than one hour.
• a LBL-type device offers a resolution typically better of the order of a millimeter but in a much longer period of time of the order of 24 hours.
• the system makes it possible to quickly reach a resolution that is certainly less than that of a device. of LBL type but which generally is sufficient for the intended applications.

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• 2013
  • 2013-06-05 FR FR1355161A patent/FR3006770B1/fr active Active
• 2014
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